Pseudomonas aeruginosa AMPR transcriptional regulatory network

In Enterobacteriaceae, the transcriptional regulator AmpR, a member of the LysR family, regulates the expression of a chromosomal β-lactamase AmpC. The regulatory repertoire of AmpR is broader in Pseudomonas aeruginosa, an opportunistic pathogen responsible for numerous acute and chronic infections including cystic fibrosis. Previous studies showed that in addition to regulating ampC, P. aeruginosa AmpR regulates the sigma factor AlgT/U and production of some quorum sensing (QS)-regulated virulence factors. In order to better understand the ampR regulon, the transcriptional profiles generated using DNA microarrays and RNA-Seq of the prototypic P. aeruginosa PAO1 strain with its isogenic ampR deletion mutant, PAOΔampR were analyzed. Transcriptome analysis demonstrates that the AmpR regulon is much more extensive than previously thought influencing the differential expression of over 500 genes. In addition to regulating resistance to β-lactam antibiotics via AmpC, AmpR also regulates non-β-lactam antibiotic resistance by modulating the MexEF-OprN efflux pump. Virulence mechanisms including biofilm formation, QS-regulated acute virulence, and diverse physiological processes such as oxidative stress response, heat-shock response and iron uptake are AmpR-regulated. Real-time PCR and phenotypic assays confirmed the transcriptome data. Further, Caenorhabditis elegans model demonstrates that a functional AmpR is required for full pathogenicity of P. aeruginosa. AmpR, a member of the core genome, also regulates genes in the regions of genome plasticity that are acquired by horizontal gene transfer. The extensive AmpR regulon included other transcriptional regulators and sigma factors, accounting for the extensive AmpR regulon. Gene expression studies demonstrate AmpR-dependent expression of the QS master regulator LasR that controls expression of many virulence factors. Using a chromosomally tagged AmpR, ChIP-Seq studies show direct AmpR binding to the lasR promoter. The data demonstrates that AmpR functions as a global regulator in P. aeruginosa and is a positive regulator of acute virulence while negatively regulating chronic infection phenotypes. In summary, my dissertation sheds light on the complex regulatory circuit in P. aeruginosa to provide a better understanding of the bacterial response to antibiotics and how the organism coordinately regulates a myriad of virulence factors.

Reverse Engineering of Modified Genes by Bayesian Network Analysis Defines Molecular Determinants Critical to the Development of Glioblastoma

In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I–IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96–100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential ‘hubs of activity’. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several ‘key genes’ may be required for the development of glioblastoma. Further studies are needed to validate these ‘key genes’ as useful tools for early detection and novel therapeutic options for these tumors.

Specific Increase in MDR1 Mediated Drug-Efflux in Human Brain Endothelial Cells following Co-Exposure to HIV-1 and Saquinavir

Persistence of HIV-1 reservoirs within the Central Nervous System (CNS) remains a significant challenge to the efficacy of potent anti-HIV-1 drugs. The primary human Brain Microvascular Endothelial Cells (HBMVEC) constitutes the Blood Brain Barrier (BBB) which interferes with anti-HIV drug delivery into the CNS. The ATP binding cassette (ABC) transporters expressed on HBMVEC can efflux HIV-1 protease inhibitors (HPI), enabling the persistence of HIV-1 in CNS. Constitutive low level expression of several ABC-transporters, such as MDR1 (a.k.a. P-gp) and MRPs are documented in HBMVEC. Although it is recognized that inflammatory cytokines and exposure to xenobiotic drug substrates (e.g HPI) can augment the expression of these transporters, it is not known whether concomitant exposure to virus and anti-retroviral drugs can increase drug-efflux functions in HBMVEC. Our in vitro studies showed that exposure of HBMVEC to HIV-1 significantly up-regulates both MDR1 gene expression and protein levels; however, no significant increases in either MRP-1 or MRP-2 were observed. Furthermore, calcein-AM dye-efflux assays using HBMVEC showed that, compared to virus exposure alone, the MDR1 mediated drug-efflux function was significantly induced following concomitant exposure to both HIV-1 and saquinavir (SQV). This increase in MDR1 mediated drug-efflux was further substantiated via increased intracellular retention of radiolabeled [3H-] SQV. The crucial role of MDR1 in 3H-SQV efflux from HBMVEC was further confirmed by using both a MDR1 specific blocker (PSC-833) and MDR1 specific siRNAs. Therefore, MDR1 specific drug-efflux function increases in HBMVEC following co-exposure to HIV-1 and SQV which can reduce the penetration of HPIs into the infected brain reservoirs of HIV-1. A targeted suppression of MDR1 in the BBB may thus provide a novel strategy to suppress residual viral replication in the CNS, by augmenting the therapeutic efficacy of HAART drugs.

Analysis of the Expression Pattern of Wnt Receptor Frizzled 3

Wnt signaling plays a vital role in many developmental processes. Wnt signaling has been implicated in neural crest induction and cell differentiation among other functions. In mice Wnts comprise a family of nineteen glycoproteins that bind to Frizzled (Fzd) receptors and LRP5/6 co-receptors. This activates beta-catenin, which translocates into the nucleus and acts as a transcription factor, resulting in differential gene expression. Specifically, Fzd 3 enhances Wnt 1 signaling. Wnt 1 and Fzd 3 are involved in neural crest induction and in neural crest-derived melanocyte development. We analyzed the expression pattern ofFzd 3 and the LRP 5/6 by in situ hybridization inmouse embryos. Our data suggests a role for these genes in neural crest induction and in melanocyte differentiation in the murine system. Results show Fzd 3 expression in the anterior part of the neural tube and in the hindbrain, while LRP 5 is expressed in the anterior part of the neural tube, in the hindbrain, and in the eye. We conclude that Fzd 3 and LRP 5 are expressed in the neural crest. In addition, Fzd 3 might act as the receptor while LRP 5 might act as the co-receptor for Wntl signaling in the murine system.

Mining the online social network data: Influence, summarization, and organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Psychosocial variables associated with the co-occurance of risky sexual behavior with alcohol consumption among university students

This study examined the association of theoretically guided and empirically identified psychosocial variables on the co-occurrence of risky sexual behavior with alcohol consumption among university students. The study utilized event analysis to determine whether risky sex occurred during the same event in which alcohol was consumed. Relevant conceptualizations included alcohol disinhibition, self-efficacy, and social network theories. Predictor variables included negative condom attitudes, general risk taking, drinking motives, mistrust, social group membership, and gender. Factor analysis was employed to identify dimensions of drinking motives. Measured risky sex behaviors were (a) sex without a condom, (b) sex with people not known very well, (c) sex with injecting drug users (IDUs), (d) sex with people without knowing whether they had a STD, and (e) sex with using drugs. A purposive sample was used and included 222 male and female students recruited from a major urban university. Chi-square analysis was used to determine whether participants were more likely to engage in risky sex behavior in different alcohol use contexts. These contexts were only when drinking, only when not drinking, and when drinking or not. The chi-square findings did not support the hypothesis that university students who use alcohol with sex will engage in riskier sex. These results added to the literature by extending other similar findings to a university student sample. For each of the observed risky sex behaviors, discriminant analysis methodology was used to determine whether the predictor variables would differentiate the drinking contexts, or whether the behavior occurred. Results from discriminant analyses indicated that sex with people not known very well was the only behavior for which there were significant discriminant functions. Gender and enhancement drinking motives were important constructs in the classification model. Limitations of the study and implications for future research, social work practice and policy are discussed.

Síntese e caracterização de nanopartículas magnéticas de Co e Ni com aplicação em magneto hipertermia

Nanoparticles are importante for the study of new phenomena and for the development of new applications. Metallic magnetic nanoparticles like Cobalt and Nickel are important for their applications in nanoscience and nanotechnology. In this work, we report on the synthesis and characterization of Ni and Co nanoparticles. The nanoparticles were prepared by the modi- ed sol-gel method and were formed in the pore-network of the biopolymer quitosan. The reduction occurred in absence of H2 ux. The metallic particles and their monoxides have a face-centered- cubic structure. The metallic particles sizes ranged from 59 to 77 nm and from 19 to 50 nm for Ni and Co, respectively. Their monoxides chemically passivated the metallic cores, and after several weeks we have not observed further increase in oxidation. The synthesis method was tuned to obtain mainly the ferromagnetic phase. The system behaves like a core/shell structure with a ferromagnetic core and an antiferromagnetic shell. Exchange bias e ect was observed at temperatures below the Néel temperature. Both systems were submitted to an alternated magnetic eld and the heat released by the particles increased the temperature to 140°C in an interval of 5 min. Similar studies in samples dispersed in water increased the temperatures to 40-59°C, these results suggest that these materials are candidates for magnetic hyperthermia.

Reference gene selection and RNA preservation protocol in the cat flea, Ctenocephalides felis, for gene expression studies

This work was supported by a Knowledge Transfer Network BBSRC Industrial Case (#414 BB/L502467/1) studentship in association Zoetis Inc.

Linking gene expression in the intestine to production of gametes through the phosphate transporter PITR-1 in Caenorhabditis elegans

Inorganic phosphate is an essential mineral for both prokaryotic and eukaryotic cell metabolism and structure. Its uptake into the cell is mediated by membrane bound transporters and coupled to Na+ transport. Mammalian sodium-dependent Pi co-transporters have been grouped into three families NaPi-I, NaPi-II, and NaPi-III. Despite being discovered more than 2 decades ago, very little is known about requirements for NaPi-III transporters in vivo, in the context of intact animal models. Here we find that impaired function of the C. elegans NaPi-III transporter, pitr-1, results in decreased brood size and dramatically increased expression of vitellogenin by the worm intestine. Unexpectedly, we found that the effects of pitr-1 mutation on vitellogenin expression in the intestine could only be rescued by expression of pitr-1 in the germline, and not by expression of pitr-1 in the intestine itself. Our results indicate the existence of a signal from the germline that regulates gene expression in the intestine, perhaps linking nutrient export from the intestine to production of gametes by the germline.

Artificial neural network nonlinear equalizer for coherent optical OFDM

We propose a novel low-complexity artificial neural network (ANN)-based nonlinear equalizer (NLE) for coherent optical orthogonal frequency-division multiplexing (CO-OFDM) and compare it with the recent inverse Volterra-series transfer function (IVSTF)-based NLE over up to 1000 km of uncompensated links. Demonstration of ANN-NLE at 80-Gb/s CO-OFDM using 16-quadrature amplitude modulation reveals a Q-factor improvement after 1000-km transmission of 3 and 1 dB with respect to the linear equalization and IVSTF-NLE, respectively.

Membrane protein extraction and purification using styrene-maleic acid (SMA) co-polymer:effect of variations in polymer structure

The use of styrene maleic acid (SMA) co-polymers to extract and purify transmembrane proteins, whilst retaining their native bilayer environment, overcomes many of the disadvantages associated with conventional detergent based procedures. This approach has huge potential for the future of membrane protein structural and functional studies. In this investigation we have systematically tested a range of commercially available SMA polymers, varying in both the ratio of styrene to maleic acid and in total size, for the ability to extract, purify and stabilise transmembrane proteins. Three different membrane proteins (BmrA, LeuT and ZipA) which vary in size and shape were used. Our results show that several polymers can be used to extract membrane proteins comparably to conventional detergents. A styrene:maleic acid ratio of either 2:1 or 3:1, combined with a relatively small average molecular weight (7.5-10 kDa) is optimal for membrane extraction, and this appears to be independent of the protein size, shape or expression system. A subset of polymers were taken forward for purification, functional and stability tests. Following a one-step affinity purification SMA 2000 was found to be the best choice for yield, purity and function. However the other polymers offer subtle differences in size and sensitivity to divalent cations that may be useful for a variety of downstream applications.

Structural and agentic analysis of supply-chains: a social network analysis approach

This research adds to a body of work exploring the role of Social Network Analysis (SNA) in the study of both relational and structural characteristics of supply chain networks. Two contrasting network cases (food enterprises and digital-based enterprises) are chosen in order to elicit structural differences in business networks subject to divergences in local embeddedness and the relative materiality of the goods and services produced. Our analysis and findings draw out differences in network structure as evidenced by metrics of network centralization and cohesion, the presence of components and other sub-groupings, and the position of central actors. We relate these structural features both to the nature of the networks and to the (qualitative) experiences of the actors themselves. We find, in particular, the role of customers as co-creators of knowledge (for the Food network), the central role of infrastructure and services (for the Digital network), the importance of ICT as a source of codified knowledge inputs, along with the continuing importance of geographical proximity for the development and transfer of tacit knowledge and for incremental learning.

Host gene expression classifiers diagnose acute respiratory illness etiology.

Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational cohort study determined whether host gene expression patterns discriminate noninfectious from infectious illness and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or noninfectious illness, as well as 44 healthy controls, was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a noninfectious cause of illness (26 probes). Overall accuracy was 87% (238 of 273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, P < 0.03) and three published classifiers of bacterial versus viral infection (78 to 83%). The classifiers developed here externally validated in five publicly available data sets (AUC, 0.90 to 0.99). A sixth publicly available data set included 25 patients with co-identification of bacterial and viral pathogens. Applying the ARI classifiers defined four distinct groups: a host response to bacterial ARI, viral ARI, coinfection, and neither a bacterial nor a viral response. These findings create an opportunity to develop and use host gene expression classifiers as diagnostic platforms to combat inappropriate antibiotic use and emerging antibiotic resistance.

Mining the Online Social Network Data: Influence, Summarization, and Organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Impacts of seawater acidification on mantle gene expression patterns of the Baltic Sea blue mussel: implications for shell formation and energy metabolism, link to supplementary material

Marine organisms have to cope with increasing CO2 partial pressures and decreasing pH in the oceans. We elucidated the impacts of an 8-week acclimation period to four seawater pCO2 treatments (39, 113, 243 and 405 Pa/385, 1,120, 2,400 and 4,000 µatm) on mantle gene expression patterns in the blue mussel Mytilus edulis from the Baltic Sea. Based on the M. edulis mantle tissue transcriptome, the expression of several genes involved in metabolism, calcification and stress responses was assessed in the outer (marginal and pallial zone) and the inner mantle tissues (central zone) using quantitative real-time PCR. The expression of genes involved in energy and protein metabolism (F-ATPase, hexokinase and elongation factor alpha) was strongly affected by acclimation to moderately elevated CO2 partial pressures. Expression of a chitinase, potentially important for the calcification process, was strongly depressed (maximum ninefold), correlating with a linear decrease in shell growth observed in the experimental animals. Interestingly, shell matrix protein candidate genes were less affected by CO2 in both tissues. A compensatory process toward enhanced shell protection is indicated by a massive increase in the expression of tyrosinase, a gene involved in periostracum formation (maximum 220-fold). Using correlation matrices and a force-directed layout network graph, we were able to uncover possible underlying regulatory networks and the connections between different pathways, thereby providing a molecular basis of observed changes in animal physiology in response to ocean acidification.